A new approach to in silico SNP detection and some new SNPs in the Bacillus anthracis genome

<p>Abstract</p> <p>Background</p> <p><it>Bacillus anthracis </it>is one of the most monomorphic pathogens known. Identification of polymorphisms in its genome is essential for taxonomic classification, for determination of recent evolutionary changes, and for evaluation of pathogenic potency.</p> <p>Findings</p> <p>In this work three strains of the <it>Bacillus anthracis </it>genome are compared and previously unpublished single nucleotide polymorphisms (SNPs) are revealed. Moreover, it is shown that, despite the highly monomorphic nature of <it>Bacillus anthracis</it>, the SNPs are (1) abundant in the genome and (2) distributed relatively uniformly across the sequence.</p> <p>Conclusions</p> <p>The findings support the proposition that SNPs, together with indels and variable number tandem repeats (VNTRs), can be used effectively not only for the differentiation of perfect strain data, but also for the comparison of moderately incomplete, noisy and, in some cases, unknown <it>Bacillus anthracis </it>strains. In the case when the data is of still lower quality, a new DNA sequence fingerprinting approach based on recently introduced markers, based on combinatorial-analytic concepts and called cyclic difference sets, can be used.</p

Genomic epidemiology of a protracted hospital outbreak caused by multidrug-resistant Acinetobacter baumannii in Birmingham, England

BACKGROUND: Multidrug-resistant Acinetobacter baumannii commonly causes hospital outbreaks. However, within an outbreak, it can be difficult to identify the routes of cross-infection rapidly and accurately enough to inform infection control. Here, we describe a protracted hospital outbreak of multidrug-resistant A. baumannii, in which whole-genome sequencing (WGS) was used to obtain a high-resolution view of the relationships between isolates. METHODS: To delineate and investigate the outbreak, we attempted to genome-sequence 114 isolates that had been assigned to the A. baumannii complex by the Vitek2 system and obtained informative draft genome sequences from 102 of them. Genomes were mapped against an outbreak reference sequence to identify single nucleotide variants (SNVs). RESULTS: We found that the pulsotype 27 outbreak strain was distinct from all other genome-sequenced strains. Seventy-four isolates from 49 patients could be assigned to the pulsotype 27 outbreak on the basis of genomic similarity, while WGS allowed 18 isolates to be ruled out of the outbreak. Among the pulsotype 27 outbreak isolates, we identified 31 SNVs and seven major genotypic clusters. In two patients, we documented within-host diversity, including mixtures of unrelated strains and within-strain clouds of SNV diversity. By combining WGS and epidemiological data, we reconstructed potential transmission events that linked all but 10 of the patients and confirmed links between clinical and environmental isolates. Identification of a contaminated bed and a burns theatre as sources of transmission led to enhanced environmental decontamination procedures. CONCLUSIONS: WGS is now poised to make an impact on hospital infection prevention and control, delivering cost-effective identification of routes of infection within a clinically relevant timeframe and allowing infection control teams to track, and even prevent, the spread of drug-resistant hospital pathogens

Eighteenth-century genomes show that mixed infections were common at time of peak tuberculosis in Europe

Tuberculosis (TB) was once a major killer in Europe, but it is unclear how the strains and patterns of infection at 'peak TB' relate to what we see today. Here we describe 14 genome sequences of M. tuberculosis, representing 12 distinct genotypes, obtained from human remains from eighteenth-century Hungary using metagenomics. All our historic genotypes belong to M. tuberculosis Lineage 4. Bayesian phylogenetic dating, based on samples with well-documented dates, places the most recent common ancestor of this lineage in the late Roman period. We find that most bodies yielded more than one M. tuberculosis genotype and we document an intimate epidemiological link between infections in two long-dead individuals. Our results suggest that metagenomic approaches usefully inform detection and characterization of historical and contemporary infections

Genetic Characterization of Conserved Charged Residues in the Bacterial Flagellar Type III Export Protein FlhA

For assembly of the bacterial flagellum, most of flagellar proteins are transported to the distal end of the flagellum by the flagellar type III protein export apparatus powered by proton motive force (PMF) across the cytoplasmic membrane. FlhA is an integral membrane protein of the export apparatus and is involved in an early stage of the export process along with three soluble proteins, FliH, FliI, and FliJ, but the energy coupling mechanism remains unknown. Here, we carried out site-directed mutagenesis of eight, highly conserved charged residues in putative juxta- and trans-membrane helices of FlhA. Only Asp-208 was an essential acidic residue. Most of the FlhA substitutions were tolerated, but resulted in loss-of-function in the ΔfliH-fliI mutant background, even with the second-site flhB(P28T) mutation that increases the probability of flagellar protein export in the absence of FliH and FliI. The addition of FliH and FliI allowed the D45A, R85A, R94K and R270A mutant proteins to work even in the presence of the flhB(P28T) mutation. Suppressor analysis of a flhA(K203W) mutation showed an interaction between FlhA and FliR. Taken all together, we suggest that Asp-208 is directly involved in PMF-driven protein export and that the cooperative interactions of FlhA with FlhB, FliH, FliI, and FliR drive the translocation of export substrate

An energy transduction mechanism used in bacterial flagellar type III protein export

Flagellar proteins of bacteria are exported by a specific export apparatus. FliI ATPase forms a complex with FliH and FliJ and escorts export substrates from the cytoplasm to the export gate complex, which is made up of six membrane proteins. The export gate complex utilizes proton motive force across the cytoplasmic membrane for protein translocation, but the mechanism remains unknown. Here we show that the export gate complex by itself is a proton–protein antiporter that uses the two components of proton motive force, Δψ and ΔpH, for different steps of the protein export process. However, in the presence of FliH, FliI and FliJ, a specific binding of FliJ with an export gate membrane protein, FlhA, is brought about by the FliH–FliI complex, which turns the export gate into a highly efficient, Δψ-driven protein export apparatus

Acquired Type III Secretion System Determines Environmental Fitness of Epidemic Vibrio parahaemolyticus in the Interaction with Bacterivorous Protists

Genome analyses of marine microbial communities have revealed the widespread occurrence of genomic islands (GIs), many of which encode for protein secretion machineries described in the context of bacteria-eukaryote interactions. Yet experimental support for the specific roles of such GIs in aquatic community interactions remains scarce. Here, we test for the contribution of type III secretion systems (T3SS) to the environmental fitness of epidemic Vibrio parahaemolyticus. Comparisons of V. parahaemolyticus wild types and T3SS-defective mutants demonstrate that the T3SS encoded on genome island VPaI-7 (T3SS-2) promotes survival of V. parahaemolyticus in the interaction with diverse protist taxa. Enhanced persistence was found to be due to T3SS-2 mediated cytotoxicity and facultative parasitism of V. parahaemolyticus on coexisting protists. Growth in the presence of bacterivorous protists and the T3SS-2 genotype showed a strong correlation across environmental and clinical isolates of V. parahaemolyticus. Short-term microcosm experiments provide evidence that protistan hosts facilitate the invasion of T3SS-2 positive V. parahaemolyticus into a coastal plankton community, and that water temperature and productivity further promote enhanced survival of T3SS-2 positive V. parahaemolyticus. This study is the first to describe the fitness advantage of GI-encoded functions in a microbial food web, which may provide a mechanistic explanation for the global spread and the seasonal dynamics of V. parahaemolyticus pathotypes, including the pandemic serotype cluster O3:K6, in aquatic environments

Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies

Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%–63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with “overprediction” of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation

Genomes of the Most Dangerous Epidemic Bacteria Have a Virulence Repertoire Characterized by Fewer Genes but More Toxin-Antitoxin Modules

We conducted a comparative genomic study based on a neutral approach to identify genome specificities associated with the virulence capacity of pathogenic bacteria. We also determined whether virulence is dictated by rules, or if it is the result of individual evolutionary histories. We systematically compared the genomes of the 12 most dangerous pandemic bacteria for humans ("bad bugs") to their closest non-epidemic related species ("controls").We found several significantly different features in the "bad bugs", one of which was a smaller genome that likely resulted from a degraded recombination and repair system. The 10 Cluster of Orthologous Group (COG) functional categories revealed a significantly smaller number of genes in the "bad bugs", which lacked mostly transcription, signal transduction mechanisms, cell motility, energy production and conversion, and metabolic and regulatory functions. A few genes were identified as virulence factors, including secretion system proteins. Five "bad bugs" showed a greater number of poly (A) tails compared to the controls, whereas an elevated number of poly (A) tails was found to be strongly correlated to a low GC% content. The "bad bugs" had fewer tandem repeat sequences compared to controls. Moreover, the results obtained from a principal component analysis (PCA) showed that the "bad bugs" had surprisingly more toxin-antitoxin modules than did the controls.We conclude that pathogenic capacity is not the result of "virulence factors" but is the outcome of a virulent gene repertoire resulting from reduced genome repertoires. Toxin-antitoxin systems could participate in the virulence repertoire, but they may have developed independently of selfish evolution

Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal